Energy systems integration, or sector coupling, has several drivers that span climate impact mitigation and economics to social and regulatory considerations. A key question is what is sector coupling, and how does it impact the flexibility of the energy system? Here, the energy system includes several sectors - electricity, gas, heat, and transportation - that have been independent for decades in most countries except for their coupling via combined heat and power (CHP) units. In energy systems integration, some sectors may provide flexibility to other sectors, while other sectors will require flexibility when interlinking. To support these synergies among sectors, it is important to explore and quantify mutual interactions as well as seek examples of how these integrations can provide flexibility and other benefits. From the perspective of the electricity sector, it is important to ensure that there is enough flexibility in the interconnected systems to support decarbonization goals, such as those set in the Paris Agreement, while ensuring operational reliability.

See publication (external link)

Decarbonisation of the electricity system requires significant and continued investment in low-carbon energy sources and electrification of the heat and transport sectors. With diminishing output and shorter operating hours of conventional large-scale fossil fuel generators, there is a growing need and opportunity for other emerging technologies to provide flexibility in the context of grid support, balancing, security services, and investment options to support a cost-effective transition to a lower-carbon energy system. This article summarises the key findings from a range of studies investigating the potential benefits and challenges associated with the future low-carbon energy system. The key challenges associated with balancing local, national and regional objectives to minimise the overall cost of decarbonising the future energy system are also discussed. Furthermore, the paper highlights the importance of cross-energy vector flexibility, and coordination across electricity, heat, and gas systems which is critical for shaping the future low-carbon energy systems. Although most of the case studies presented in this article are based on the UK, and to some extent the EU decarbonisation pathways, the overall conclusions regarding the value of flexibility are relevant for the global energy transition.

See publication (external link)

A major challenge to develop optimal strategies for allocation of flexible demand towards the smart grid paradigm is the uncertainty associated with the real‐time price and electricity demand. This paper presents a regret‐based model and a novel iterative algorithm which solves the minimax regret optimization problem. This algorithms exhibits low computational burden compared with traditional linear programming methods and affords iterative convergence through updates of feasible power schedules, thus enabling a scalable parallel implementation for large device populations. Specifically, our approach seeks to minimize the induced worst‐case regret over all price scenarios and solves the optimal charging strategy for the electrical devices. The convergence of the method and optimality of the computed solution is justified and some numerical simulations are discussed for the case of a single device operating under different types of price realizations and uncertainty bounds.

See publication (external link)

This paper proposes a novel decentralised control approach dedicated to coordinating the operation of a large population of residential thermal energy storage characterised by diversified specifications, while innovatively considering the operational constraints on both the national and the local level. The presented iterative algorithm sequentially updates the storage operational schedule under the real-time electricity price scheme to achieve cost savings for each individual participant and the total system, while effectively avoiding the violation of local distribution network restrictions. The transmission topology is explicitly considered to investigate the impacts of transmission congestion on the electricity marginal prices. The results of a series of case studies demonstrate that the proposed coordination approach can effectively enable individual energy arbitrage and achieve 22.53 % system cost savings compared to the 10.34 % savings when coordination is absent. Moreover, the simulation results manifest that the coordinated control approach can cost-effectively perform distribution congestion management to ensure no local network is overloaded, which will cause 12.3 % increase in system operational costs. Overall, through coordinating the operation of numerous residential thermal energy storage to perform both energy arbitrage and distribution network congestion management, the proposed control approach can benefit the system operation at both the national and local levels.

See publication (external link)

Demand-side response from space heating in residential buildings can potentially provide a huge amount of flexibility for the power system, particularly with deep electrification of the heat sector. In this context, this paper presents a novel distributed control strategy to coordinate space heating across numerous residential households with diversified thermal parameters. By employing an iterative algorithm under the game-theoretical framework, each household adjusts its own heating schedule through demand shift and thermal comfort compensation with the purpose of achieving individual cost savings, whereas the aggregate peak demand is effectively shaved on the system level. Additionally, an innovative thermal comfort model which considers both the temporal and spatial differences in customised thermal comfort requirements is proposed. Through a series of case studies, it is demonstrated that the proposed space heating coordination strategy can facilitate effective energy arbitrage for individual buildings, driving a 13.96% reduction in system operational cost and 28.22% peak shaving. Moreover, the superiority of the proposed approach in thermal comfort maintenance is numerically analysed based on the proposed thermal comfort quantification model.

See publication (external link)

The electrification of transport seems inevitable as part of global decarbonization efforts, but power system integration of electric vehicles faces numerous challenges, including a disproportionately high demand peak necessitating expensive infrastructure investments. Moreover, long-term developments in the power sector are characterized by great uncertainty, which increases the risk of making incorrect investment decisions leading to stranded assets. A cost-effective system integration of electrified transport would therefore not be possible without the implementation of smart charging concepts in combination with strategic network expansion planning that considers the impact of uncertainties. This paper proposes investment and operation models of Grid-to-Vehicle (G2V), Vehicle-to-Grid (V2G), and Vehicle-to-Building (V2B) for the large-scale and long-term network expansion planning problem under multi-dimensional uncertainty. Additionally, it presents a multi-stage stochastic planning framework that can identify optimal investment strategies such that the expected system cost is minimized and the risk of stranded investments is reduced. The models are demonstrated on the IEEE 24-bus test system and applied in a case study of the power system of Great Britain. The results highlight G2V, V2G and V2B as effective non-network alternatives to conventional reinforcement that could generate substantial economic savings and act as hedging instruments against uncertainty. For the case of Great Britain, the Option Values of G2V, V2G, and V2B could amount to £1.2bn, £10.8bn, and £10.1bn, respectively, over a 40-year horizon. Although the quantified values are system-specific, the paper presents key observations on the role of smart charging concepts as investment options that can be generalized for any low-carbon power system.

See publication (external link)

Thermal energy storage (TES) is widely expected to play an important role in facilitating the decarbonization of the future energy system. Although significant work has been done in assessing the values of traditional sensible TES, less is known about the role, impact and value of emerging advanced TES at the system level. This is particularly the case of latent heat thermal energy storage (LHTES) and thermochemical energy storage (TCS). In this context, this paper is dedicated to evaluating the techno-economic values for the whole UK energy system of LHTES and TCS technology using an integrated whole energy system model. First, the key concepts of the whole system modelling framework are introduced. Unique to this work is that the economic benefits delivered by LHTES and TCS to different levels of the UK energy system infrastructure and various energy sectors through the deployment of TES are explicitly analysed, which comprehensively demonstrates the values of selected TES technologies from the whole system perspective. A series of sensitivity studies are implemented to analyse the advantages and disadvantages of LHTES and TCS under different conditions. The simulation results indicate that TES can benefit different sectors of the whole energy system and drive significant cost savings, but the whole system values of TES is closely dependent on the decarbonization requirement. Although LHTES is characterized by relatively low capital costs, when TES penetration is limited and carbon target is tight, the advantage of TCS is outstanding due to its high energy density.

See publication (external link)

Electric Vehicle (EV) penetration is rapidly increasing across the world and utilization of these in vehicle-to-grid (V2G) services can provide benefits to not just operation costs, but also resilience. To optimize the operation of EVs, as well as other local generation, demand and storage, the concept of microgrids has widely been used in the literature for smart control of local resources. During disruptive events such as microgrid islanding, EVs can act similarly to battery storage to minimize loss of critical loads. In this paper, day-ahead schedules are generated for EV operation in an urban multi-energy microgrid (MEMG) every 15 minutes for a 24-hour period. At each 15-minute timestep, individual EVs are updated based on a rolling EV dispatch strategy and real time data is fed back into the day-ahead schedule. After a predetermined time, an outage causes the microgrid to enter islanded mode. The combined and individual benefits of preventive and corrective control of EVs in increasing resilience is assessed, in addition to a comparison of the value of two novel rolling EV dispatch strategies. Results show that both control strategy and EV dispatch strategy can have a considerable effect on resilience enhancement provided by EVs.

See publication (external link)

Coordinated preheating can potentially enhance the flexibility of the electricity system, thereby driving significant economic savings. In this context, this paper proposes a novel game-theory based preheating coordination scheme aimed at guaranteeing the effectiveness of collective preheating performed by a large population of households. By adopting an innovative two-phase iterative algorithm, individual households autonomously schedule their heating power allocation to seek for savings in energy bills while smartly maintaining thermal comfort. Meanwhile, the total electricity generation cost decreases at each iteration and converges to an equilibrium solution asymptotically. Compared to the centralised optimization-based energy management control methods, the proposed algorithm effectively reduces the information exchange while significantly reduces computational complexity. The simulation results indicate that the proposed coordination strategy can drive 12.30% cost saving when all households participate in the preheating scheme whereas 11.35% cost increase will be incurred if coordination is absent. Overall, the proposed preheating control algorithm simultaneously benefits both individual households and the whole system by intelligently linking local behaviour with global interests.

See publication (external link)

The electrification of transport is expected to cause an increase in electrical demand and necessitate significant network investments to accommodate it. However, due to considerable uncertainty over long-term power system developments, there is a need for investment options that offer managerial flexibility and for planning frameworks that can exploit it. This paper presents the application of a multi-stage stochastic planning framework that captures multi-dimensional uncertainty, integrates Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) as smart investment alternatives, and quantifies their Option Values. The case studies on the power system of Great Britain, highlight the significant value of G2V and V2G as investment options and demonstrate the wider system benefits of their integration, including effects on renewable generation curtailment and CO2 emissions. The observations can be generalized for any power system with large penetration of renewable generation and provide evidence for the idea of planning with G2V and V2G to relevant stakeholders.

See publication (external link)

The electrification of transport seems inevitable as part of global decarbonization efforts, but power system integration of electric vehicles faces numerous challenges, including a disproportionately high demand peak necessitating expensive infrastructure investments. Moreover, long-term developments in the power sector are characterized by great uncertainty, which increases the risk of making incorrect investment decisions leading to stranded assets. A cost-effective system integration of electrified transport would therefore not be possible without the implementation of smart charging concepts in combination with strategic network expansion planning that considers the impact of uncertainties. This paper proposes investment and operation models of Grid-to-Vehicle (G2V), Vehicle-to-Grid (V2G), and Vehicle-to-Building (V2B) for the large-scale and long-term network expansion planning problem under multi-dimensional uncertainty. Additionally, it presents a multi-stage stochastic planning framework that can identify optimal investment strategies such that the expected system cost is minimized and the risk of stranded investments is reduced. The models are demonstrated on the IEEE 24-bus test system and applied in a case study of the power system of Great Britain. The results highlight G2V, V2G and V2B as effective non-network alternatives to conventional reinforcement that could generate substantial economic savings and act as hedging instruments against uncertainty. For the case of Great Britain, the Option Values of G2V, V2G, and V2B could amount to £1.2bn, £10.8bn, and £10.1bn, respectively, over a 40-year horizon. Although the quantified values are system-specific, the paper presents key observations on the role of smart charging concepts as investment options that can be generalized for any low-carbon power system.

See publication (external link)

The anticipated electrification of the transport sector may lead to significant increase in the future peak electricity demand, resulting in potential violations of network constraints. As a result, a considerable amount of network reinforcement may be required in order to ensure that the expected additional demand from electric vehicles that are to be connected will be safely accommodated. In this paper we present the Backwards Induction Framework (BIF), which we use for identifying the optimal investment decisions, for calculating the option value of smart charging of EV and the cost of stranded assets; these concepts are crystallized through illustrative case studies. Sensitivity analyses depict how the option value of smart charging and the optimal solution are affected by key factors such as the social cost associated with not accommodating the full EV capacity, the flexibility of smart charging, and the scenario probabilities. Moreover, the BIF is compared with the Stochastic Optimization Framework and key insights are drawn.

See publication (external link)

The ongoing electrification of the heat and transport sectors is expected to lead to a substantial increase in peak electricity demand over the coming decades, which may drive significant investment in network reinforcement in order to maintain a secure supply of electricity to consumers. The traditional way of security provision has been based on conventional investments such as the upgrade of the capacity of electricity transmission or distribution lines. However, energy storage can also provide security of supply. In this context, the current paper presents a methodology for the quantification of the security contribution of energy storage, based on the use of mathematical optimization for the calculation of the F-factor metric, which reflects the optimal amount of peak demand reduction that can be achieved as compared to the power capability of the corresponding energy storage asset. In this context, case studies underline that the F-factors decrease with greater storage power capability and increase with greater storage efficiency and energy capacity as well as peakiness of the load profile. Furthermore, it is shown that increased investment in energy storage per system bus does not increase the overall contribution to security of supply.

See publication (external link)

Decarbonisation and climate change targets require multiscale sociotechnical energy transitions that include significant changes to housing stock. In the UK, the development of Active Buildings, which directly seek to be efficient energy producers, have zero carbon emissions and provide grid flexibility, has the potential to make a significant contribution to meeting these targets. Active Homes as a particular type of Active Building represent a potentially transformational innovation by altering how energy is produced, distributed and consumed, in addition to how homes are designed, constructed and then lived in. In this paper we draw on insights from qualitative interviews with stakeholders involved in the development of different Active Homes to consider motivations for development, and their views on how residents will reside in and interact with the homes. We highlight a potential conflict between a desire to prioritise the needs of residents with a belief amongst some that to do so, user engagement with technology should be minimised. This has implications for design decisions, which in turn influence how residents experience and live within the homes. In illuminating these narratives, we indicate the necessity of ongoing engagement with residents to understand how Active Homes – with particular emphasis on the operation and control of technologies – are experienced, in order to inform the successful rollout of current and future developments.

See publication (external link)

In this paper, we develop an optimization-based systematic approach for the challenging, less studied, and important problem of optimal partitioning of multi-thermal zone buildings for the decentralized control. The proposed method consists of (i) construction of a graph-based network to quantitatively characterize the thermal interaction level between neighbour zones, and (ii) the application of two different approaches for optimal clustering of the resulting network graph: stochastic optimization and robust optimization. The proposed method was tested on two case studies: a 5-zone building (a small-scale example) which allows one to consider all possible partitions to assess the success rate of the developed method; and a 20-zone building (a large-scale example) for which the developed method was used to predict the optimal partitioning of the thermal zones. Compared to the existing literature, our approach provides a systematic and potentially optimal solution for the considered problem

See publication (external link)

Buildings are responsible for about a quarter of global energy-related CO2 emissions. Consequently, the decarbonisation of the housing stock is essential in achieving net-zero carbon emissions. Global decarbonisation targets can be achieved through increased efficiency in using energy generated by intermittent resources. The paper presents a co-design framework for simultaneous optimal design and operation of residential buildings using Model Predictive Control (MPC). The framework is capable of explicitly taking into account operational constraints and pushing the system to its efficiency and performance limits in an integrated fashion. The optimality criterion minimises system cost considering time-varying electricity prices and battery degradation. A case study illustrates the potential of co-design in enhancing flexibility and self-sufficiency of a system operating under different conditions. Specifically, numerical results from a low-fidelity model show substantial carbon emission reduction and bill savings compared to an a-priori sizing approach.

See publication (external link)

New advances in small-scale generation and consumption technologies have shifted conventional buildings’ functionality towards energy-efficient active buildings (ABs). Such developments drew the attention of researchers all around the world, resulting in a variety of publications, including several review papers. This study conducts a systematic literature review so as to analyse the concepts/factors enabling active participation of buildings in the energy networks. To do so, a relatively large number of publications devoted to the subject are identified, introducing the taxonomy of control and optimisation methods for the ABs. Then, a study selection methodology is proposed to nominate potential literature that has investigated the role of ABs in the energy networks. The modelling approaches in enabling flexible ABs are identified, while the potential challenges have been highlighted. Furthermore, the citation network of included papers is illustrated by Gephi software and analysed using “ForceAtlas2” and “Yifan Hu Proportional” algorithms so as to analyse the insights and possibilities for future developments. The survey results provide a clear answer to the research question around the potential flexibility that can be offered by ABs to the energy grids, and highlights possible prospective research plans, serving as a guide to research and industry.New advances in small-scale generation and consumption technologies have shifted conventional buildings’ functionality towards energy-efficient active buildings (ABs). Such developments drew the attention of researchers all around the world, resulting in a variety of publications, including several review papers. This study conducts a systematic literature review so as to analyse the concepts/factors enabling active participation of buildings in the energy networks. To do so, a relatively large number of publications devoted to the subject are identified, introducing the taxonomy of control and optimisation methods for the ABs. Then, a study selection methodology is proposed to nominate potential literature that has investigated the role of ABs in the energy networks. The modelling approaches in enabling flexible ABs are identified, while the potential challenges have been highlighted. Furthermore, the citation network of included papers is illustrated by Gephi software and analysed using “ForceAtlas2” and “Yifan Hu Proportional” algorithms so as to analyse the insights and possibilities for future developments. The survey results provide a clear answer to the research question around the potential flexibility that can be offered by ABs to the energy grids, and highlights possible prospective research plans, serving as a guide to research and industry.

See publication (external link)

Energy systems are undergoing radical changes that have resulted in buildings being regarded as proactive players with the potential to contribute positively to energy networks. This study investigates the role of active buildings (ABs) as prosumers in energy systems by introducing a building-to-building (B2B) strategy for energy exchange between residential units, as well as a building-for-grid (B4G) model by exploiting the demand flexibility of residential microgrids (RMGs). The mid-market rate mechanism is adopted to produce local market price signals at RMG level. A robust rolling horizon controller is developed for real-time energy management of a community of ABs. This control philosophy can improve the robustness of the RMG in face of real-time weather and energy price prediction errors. The proposed method is a multi-level optimisation which pursues multiple goals while making a trade-off between operational cost and occupant comfort. Finally, the repercussions of COVID-19 induced power consumption resulting from changing lifestyle and building occupancy profile is analysed by the proposed method as a case study. The results show that the proposed B2B and B4G strategy can reduce energy bills by 18.45%, while notable robust real-time control and computational efficiencies are achieved when benchmarked against conventional methods.

See publication (external link)

Global electric vehicles (EVs) fleet is expanding at a rapid pace. Considering the uncertain driving pattern of EVs, they are dynamic consumers of electricity and their integration can give rise to operational problems and jeopardize the security of the power system. Under such circumstances, the implementation of demand-side response (DSR) programs is more likely to be an effective solution for reducing the risks of load curtailment or security problems. This study proposes a voltage stability constrained DSR-coordinated planning model for increasing the penetration level of EVs in a distribution system consisting of photovoltaics (PVs), wind turbines (WTs) and responsive loads. The uncertainties of PV/WT generation, the driving pattern of EVs, and load demand are modeled by an improved form of information gap decision theory (IGDT), hereafter called weighted IGDT (WIGDT). Due to the fact that the proposed model is nonlinear and non-convex, a linearization technique is adopted and the proposed model is formulated as a mixed-integer linear programming (MILP), solved using the general algebraic modeling system (GAMS) software. The standard 33-bus distribution test system and a real-world smart distribution network, based in the Isle of Wight in the UK, are used to evaluate the performance of the model.

See publication (external link)

Solid walls are a common feature of the pre-1919 Victorian housing stock in England, however their construction results in considerable heat loss, and thus large heating requirements. Solid wall insulation of these walls would improve energy efficiency, and in turn should reduce greenhouse gas emissions. However, the additional insulation needed comes with an embodied carbon cost. Current studies about whole life performance of solid wall insulation focus on a single building or building type only, without considering the diversity of building types in the pre-1919 Victorian house stock. This study fills this gap by investigating the whole life carbon performance of eight current market available insulation materials. The insulation materials studied include vacuuminsulated panels (VIPs), aerogel, phenolic foam, polyurethane (PUR), polyisocyanurate (PIR), expanded polystyrene (EPS), glass wool and wood fibre. The results show that solid wall insulation reduces whole life carbon emissions up to 1654 kgCO2e per m2, with the carbon payback time of all eight insulation materials being less than 23 years in the worst case scenario, and less than one year in the best case scenario. Both are considerably shorter than the service life of the insulation materials. More actions should be taken to promote the installation of solid wall insulation in the pre-1919 Victorian house stock as this work shows that the accumulated carbon reduction potential reached 268 MtCO2e from 2021 to 2050.

See publication (external link)

The energy sector, and buildings in particular, are one of the main contributors to climate change. Demand-Side Management (DSM) has the potential to realise energy savings on the demand as well as the supply side. However, the domestic sector still presents a major challenge due to its complex nature, one of which is the element of human interaction. A series of case studies comparing different user interface designs were undertaken to investigate domestic Demand Response (DR) in relation to automated washing appliances and their effects on occupants. Focus groups were used to inform the study design and to cross-validate case study findings. The aim was to identify factors that may influence adoption and implementation of DR, in particular incentives and feedback methods. The results highlighted the importance of the intrinsic features of the controlled appliances as well as the wider social and physical environments they were operated in. The dynamics within households with limited resources, such as time and space, meant that convenience was key regarding DR system adoption, whilst financial incentives were suitable for initial user attraction. Dynamic pricing, commonly featured in DSM systems, was also shown to stress household practices and to cause both, efficient and inefficient energy use, if coupled with automation. Furthermore, the agency, clarity and reliability of control and feedback mechanisms were found to be crucial with regards to DR acceptance. The study suggests that convenience, including ease of system operation and household practice integration, should be DR's primary guiding design principle.

See publication (external link)

The technology integrated in modern smart infrastructures makes them vulnerable to malicious cyber attacks and misuse of information systems. Active Buildings (AB) are no exception. AB implement the vision of 'buildings as power stations', aiming for operational efficiency in generation, storage, release, and conservation of energy collaboratively among neighbouring smart buildings. However, adversaries may exploit cyber-physical vulnerabilities on the smart infrastructure to cause service interruptions or financial losses. For this reason, it is imperative to effectively respond and devise countermeasures to deter attacks. This work presents a roadmap to guide AB's cybersecurity efforts, adapting existing mechanisms in enterprise information systems, Cyber-Physical Systems, Internet-of-Things, and Industrial Control Systems. We aim to help power and building managers to understand trade-offs to assess risk, model threats, deploy intrusion detection, or simulate the infrastructure. Our contribution also discusses open research questions with respect to cybersecurity, highlighting needed developments for hardening AB and thwarting attacks.

See publication (external link)

Electric Vehicles (EVs) can help alleviate our reliance on fossil fuels for transport and electricity systems. However, charging millions of EV batteries requires management to prevent overloading the electricity grid and minimise costly upgrades that are ultimately paid for by consumers. Managed chargers, such as Vehicle-to-Grid (V2G) chargers, allow control over the time, speed and direction of charging. Such control assists in balancing electricity supply and demand across a green electricity system and could reduce costs for consumers. Smart and V2G chargers connect EVs to the power grid using a charging device which includes a data connection to exchange information and control commands between various entities in the EV ecosystem. This introduces data privacy concerns and is a potential target for cyber-security attacks. Therefore, the implementation of a secure system is crucial to permit both consumers and electricity system operators to trust smart charging and V2G. In principle, we already have the technology needed for a connected EV charging infrastructure to be securely enabled, borrowing best practices from the Internet and industrial control systems. We must properly adapt the security technology to take into account the challenges peculiar to the EV charging infrastructure. Challenges go beyond technical considerations and other issues arise such as balancing trade-offs between security and other desirable qualities such as interoperability, scalability, crypto-agility, affordability and energy efficiency. This document reviews security and privacy topics relevant to the EV charging ecosystem with a focus on smart charging and V2G.

See publication (external link)

Domestic zonal heating controls enable hydronic systems to heat rooms to different temperatures at different times. The first credible evidence known to the authors, of the in-use energy savings of such controls, is reported. The results and research methods are globally relevant. The energy demands and room temperatures in 68, gas-heated, owner-occupied, semi-detached homes, in the English Midlands were monitored for a year before zonal controls were fitted in 37 of the homes prior to the second year of monitoring. The other homes retained the existing heating controls and so provided a matched (control) group. Surveys and questionnaires characterised the dwellings, heating systems and households. In two thirds of the homes with zonal controls the annual gas demand decreased, in one third it increased. Overall, the mean gas demand decreased by 3.5% relative to the homes that retained their existing controls. Savings were achieved primarily by reducing bedroom temperatures, especially in the evenings. Wireless, digital zonal controls are unlikely to provide an acceptable payback through reductions in energy bills at today’s prices, but they offer households the flexibility to react to time-of-use energy pricing. A matched (control) group is essential for the reliable calculation of energy demand changes arising from interventions in occupied homes.

See publication (external link)

Heating homes using gas boilers is incompatible with the UK’s target of net-zero greenhouse gas emissions by 2050. One solution is to shift to heat pumps (HPs) supplied from decarbonised power plant, but this could place an unmanageable burden on the electricity supply network. National heat demand profiles depend on the heating patterns adopted by households which, in turn, depend on the type of heating system and its control. The largest data sets available, from around 6600 gas-heated homes and 600 homes with HPs, are used to create an empirical model of Great Britain’s (GB) half-hourly domestic heat demand. The model is used to estimate the annual half-hourly heat demand of the GB housing stock for both current and future weather conditions. The demand profile when using HPs is compared to the current profile for gas heating. In a cold year, the calculated total annual heat demand of a typical mix of ground source and air-source HPs was 422TWh, 8% greater for than for gas-heated homes. However, the peak heat demand of 157GW was 8% lower than for gas heating, and the maximum heat ramp rate of 21GW/h, 67% lower. These results are due to the different ways that households use gas boilers and HPs. The accurate modelling of heating patterns is necessary to achieve reliable predictions of national heat demand. Policy initiatives, financial incentives or other interventions that influence the daily pattern of HP usage could also have a marked and positive influence on the GB heat demand profile.

See publication (external link)

Thermochemical energy storage (TCES) has attracted significant attention in recent years due to some unique features of the technology such as very high energy density and negligible heat loss during storage. The TCES, however, is still at its early stage of development currently at a technology readiness level of 1–3. Major technical challenges of the TCES include materials stability, charge/discharge kinetics and limited temperature lift. Here we firstly studied the application of shell-and-tube thermochemical reactor with silica gels as heat storage material in open TCES system by experimental method. And then validated model (the maximum root mean square percentage error of 13.62% between the modeling and experiments) of single tube reactor containing 0.29 kg silica-gel was established to numerically investigate the discharging behavior of the thermochemical reactor under different operating conditions and flow directions of air and water. The numerical simulation results showed inverse heat transfer occurred for a counter-flow of air-water. The problem could be solved by changing the counter-flow of air and water to the parallel-flow. Thus, the water outlet maximum temperature limit was broken through. The total heat uptake increased by at least 24.14% when water flow rate was less than 0.36 kg/h and 11.93% when air flow rate was more than 1.07 kg/h, respectively. By increasing the inlet temperature of air and water from 23°C to 38°C, the maximum temperature lift could be significantly increased by 79.94% for air and 80.81% for water, respectively. Meanwhile, the total heat uptake increased by 107.44%. For a completely charging and discharging process, the discharging rate of parallel-flow was faster than that of counter-flow.

See publication (external link)

Since early-stage decisions have the largest impact on climate related emissions, if modelling is to help deliver zero carbon designs, tools are needed that can be used by those involved at this stage. By contrast, tools that require a detailed description of the building or a specialist have less usefulness at this point in the design cycle. So, just how simple can models be (mathematically and interface-wise), to give meaningful answers to decisions such as the shape of the building and the glazing ratio? The ideal tool would be pedagogical and leave the user with knowledge that they could apply even earlier to the next project. In this work we present ZEBRA, a highly simplified, quick-to-use, model for scoping zero-carbon buildings. The model only requires approximately 33 inputs, no training, considers embodied emissions and renewables and leaves the user upskilled on zero carbon design. The predictions from 5 very low energy buildings placed into 559 climates obtained by this new model are compared to the leading model for high-performing buildings. The average difference was 0.9 kWh·m−2·a−1 (SD = 0.6). The mean time taken to model a building by someone not previously exposed to ZEBRA was 35 min (SD = 8), and 17 min (SD = 3) on second use. Therefore, ZEBRA is highly accurate when compared to the best-in-class tool and can be used quickly by the uninitiated. Hence ZEBRA has the potential to be highly useful as a first-pass tool whilst simultaneously rapidly upskilling the industry.

See publication (external link)

The cover glass on solar modules provides protection for the underlying solar cells but also leads to two forms of power loss: reflection losses and soiling losses. In this work we explore the addition of a thin hydrophobic layer of refractive index n=1.35 to the outer surface of a broadband multilayer anti-reflection (MAR) coating, comparing modelling with the actual performance of the coating. Systems with hydrophobic layers from 5nm to 300nm in thickness deposited on the surface of a broadband AR coating have been modelled, with reflectance curves and weighted average reflection (WAR) calculations showing that the total reflection stays below that of uncoated glass at all thicknesses. However, the optimal coating is determined to be ∼5nm in thickness. Addition of the hydrophobic layer increases the water contact angle of the MAR coating from 7° to 114°, with a significant increase in anti-soiling properties. This provides proof of principle of the benefits of combining a high performance AR coating with a hydrophobic anti-soiling coating on module cover glass.

See publication (external link)

One of the most important challenges faced by solar asset managers is the accumulation of soiling and cementation on the photovoltaic module glass cover. Soiling attenuates the incident light and can severely reduce the output power. Hydrophobic coatings applied to the cover glass have the potential to reduce the amount of soiling by reducing surface energy and adhesion. Their presence should make the modules easier to clean. However, there are concerns that the currently available coatings degrade in an unacceptably short time of service in the field. It is important that the mechanisms of degradation are understood, with limited time to perform outdoor testing on hydrophobic coatings, accelerated laboratory-based environmental exposure tests are also conducted. This study evaluates the effectiveness of these accelerated environmental exposure tests and compares the degradation mechanisms observed in ultraviolet (UV) and damp heat (DH) exposure, to how they compare and correlate with long-term outdoor counterparts. The results from surface chemical characterisation show that all forms of testing result in a decrease in fluorine. Conversely oxygen and silicon increase over time as the thickness of the hydrophobic film is reduced and more of the glass substrate is exposed as observed in X-ray Photoelectron Spectroscopy. UV exposure was found to cause free radicalization leading to chain scission and detachment of fluorinated functional groups. Likewise, damp heat caused chain scission via hydrolysis. UV degradation was the primary factor of outdoor exposure with added factors such as environmental abrasion causing accelerated damage of the hydrophobic coating.

See publication (external link)

In March 2020, the United Kingdom (UK) government ruled that householders must stay home as a response to the COVID-19 outbreak to help flatten the curve of the epidemic and reduce the exponential growth of the virus. Commercial activities, workplaces and schools were obliged to temporarily close in compliance with the government rules. This first and most restrictive lockdown took place from late March to early May 2020 when occupants had to stay in their homes except for very restricted essential activities. Two other lockdowns were introduced in November 2020 and January 2021, alongside with a range of restrictive measures during 2020. This offered an unprecedented opportunity to investigate the impact of a prolonged period of occupancy on household electricity consumption. In this work, the authors compared electricity consumption data collected from 21 energy-efficient houses in Nottingham, UK, during these lockdown periods to the same period in the previous year. The findings indicated that the monthly electricity consumption in April 2020, during the strictest lockdown, increased approximately 7% in comparison to the same period in 2019. Hourly average electrical power demand profile during this lockdown showed earlier and longer peaks in the evenings with the emergence of a new midday peak in comparison to typical daily peaks prior to lockdown. Total electricity consumption increased by 17% in 2020–2021, when restrictive measures were in place.

See publication (external link)

This paper proposes a novel decentralised control approach dedicated to coordinating the operation of a large population of residential thermal energy storage characterised by diversified specifications, while innovatively considering the operational constraints on both the national and the local level. The presented iterative algorithm sequentially updates the storage operational schedule under the real-time electricity price scheme to achieve cost savings for each individual participant and the total system, while effectively avoiding the violation of local distribution network restrictions. The transmission topology is explicitly considered to investigate the impacts of transmission congestion on the electricity marginal prices. The results of a series of case studies demonstrate that the proposed coordination approach can effectively enable individual energy arbitrage and achieve 22.53 % system cost savings compared to the 10.34 % savings when coordination is absent. Moreover, the simulation results manifest that the coordinated control approach can cost-effectively perform distribution congestion management to ensure no local network is overloaded, which will cause 12.3 % increase in system operational costs. Overall, through coordinating the operation of numerous residential thermal energy storage to perform both energy arbitrage and distribution network congestion management, the proposed control approach can benefit the system operation at both the national and local levels.

See publication (external link)

The electrification of transport seems inevitable as part of global decarbonization efforts, but power system integration of electric vehicles faces numerous challenges, including a disproportionately high demand peak necessitating expensive infrastructure investments. Moreover, long-term developments in the power sector are characterized by great uncertainty, which increases the risk of making incorrect investment decisions leading to stranded assets. A cost-effective system integration of electrified transport would therefore not be possible without the implementation of smart charging concepts in combination with strategic network expansion planning that considers the impact of uncertainties. This paper proposes investment and operation models of Grid-to-Vehicle (G2V), Vehicle-to-Grid (V2G), and Vehicle-to-Building (V2B) for the large-scale and long-term network expansion planning problem under multi-dimensional uncertainty. Additionally, it presents a multi-stage stochastic planning framework that can identify optimal investment strategies such that the expected system cost is minimized and the risk of stranded investments is reduced. The models are demonstrated on the IEEE 24-bus test system and applied in a case study of the power system of Great Britain. The results highlight G2V, V2G and V2B as effective non-network alternatives to conventional reinforcement that could generate substantial economic savings and act as hedging instruments against uncertainty. For the case of Great Britain, the Option Values of G2V, V2G, and V2B could amount to £1.2bn, £10.8bn, and £10.1bn, respectively, over a 40-year horizon. Although the quantified values are system-specific, the paper presents key observations on the role of smart charging concepts as investment options that can be generalized for any low-carbon power system.

See publication (external link)

A class of data-driven control methods has recently emerged based on Willems' fundamental lemma. Such methods can ease the modelling burden in control design but can be sensitive to disturbances acting on the system under control. In this paper, we extend these methods to incorporate segmented prediction trajectories. The proposed segmentation enables longer prediction horizons to be used in the presence of unmeasured disturbance. Furthermore, a computation time reduction can be achieved through segmentation by exploiting the problem structure, with computation time scaling linearly with increasing horizon length. The performance characteristics are illustrated in a set-point tracking case study in which the segmented formulation enables more consistent performance over a wide range of prediction horizons. The computation time for the segmented formulation is approximately half that of an unsegmented formulation for a horizon of 100 samples. The method is then applied to a building energy management problem, using a detailed simulation environment, in which we seek to minimise the discomfort and energy of a 6-room apartment. With the segmented formulation, a 72% reduction in discomfort and 5% financial cost reduction is achieved, compared to an unsegmented formulation using a one-day-ahead prediction horizon.

See publication (external link)

Data driven approaches have been widely employed in recent years to detect electricity thefts. Although many techniques have been proposed in the literature, they mainly focus on electricity thefts by consumers of power from the grid. Existing studies do not consider electricity thefts by prosumers , who act as both supplier and consumer in the energy system. This is of great importance as inaccurate reports of prosumers' behaviours can disturb power system operation. Here, the paper examines the role prosumers may play in subverting the energy system and propose a novel means of detecting such malfeasance. Specifically, this work introduces a new electricity theft attack scenarios called balance attacks , where an attacker concurrently modifies his readings along with neighbouring meters in an attempt to balance the total aggregated reading. Such attacks can be difficult to detect by existing solutions that reach detection decisions based on aggregated readings. A novel electricity theft detector is proposed that can detect thefts in the presence of prosumers. Current approaches use either a single model for all users across the system or else a model for each user. Here, a half-way house approach is adopted where a cluster-based detection model is used. In each cluster, the power time series for a user is decomposed into trend, cyclical and residual components. Residual data, along with different features from multiple data sources, are fed in an ML classification algorithm to detect anomalous readings. Simulations have been conducted using a newly generated dataset and results have shown that the proposed model can detect electricity theft with high detection and low error rates. The results also shows that the proposed model can detect thefts with great accuracy from new users.

See publication (external link)

Sorption based thermochemical energy storage using salt hydrates offers several potential advantages if engineered properly, compared with sensible and latent heat storage technologies, including low heat loss, small volume change and high energy density. Two of key technological challenges are low mechanical structure stability, which determines the life-span; and slow charging and discharging kinetics, which depends largely on mass and heat transfer. As the heat and mass transfer relates to structure and composition of thermochemical storage materials, the two key challenging aspects are coupled and the use of engineered composite thermochemical materials provides an avenue to address the challenges. In this paper, we report a novel thermochemical storage composite material, consisting of magnesium sulfate (MgSO4, the thermochemical storage material) and expanded graphite (EG, heat transfer enhancer and structural stabiliser), prepared by impregnation of MgSO4 into EG. The composite has been characterized by various methods, including scanning electron microscopy (SEM), differential scanning calorimeter (DSC), thermogravimetry (TG), transient plane heat source method and dynamic vapor sorption (DVS). The results showed that the MgSO4-EG composite containing 60% MgSO4 displayed superior heat and mass transfer properties. The hydration time of MgSO4 was shorten to about 1/4 of its pure and original form and the thermal conductivity was increased by more than 84.8% through the MgSO4 impregnation into EG.

See publication (external link)

Thermochemical storage (TCS) offers a number of advantages over sensible and latent heat based thermal energy storage (TES) technologies, including low heat loss, small volume change and high energy density. However, two of key technological challenges are low cycle stability and slow charging and discharging kinetics. We report here a novel composite TCS material made from MgSO4 and diatomite using an impregnation method. The structures, sorption kinetics, thermal properties and cycle stability of the composite were investigated by using several analytical techniques including scanning electron microscope, surface area measurements, Raman microscope, thermal gravitational analyzer, dynamic vapor sorption analyzer and differential scanning calorimeter. The results show that the porous structure of the diatomite provides water vapor transport channels and contact area between water vapor and MgSO4, leading to an increased hydration rate of MgSO4, hydration state and cycle stability compared with pure MgSO4, and an improved sorption capacity and thermal performance. When MgSO4 in the composites reaches ∼60% by mass, the diatomite tends to be saturated with more MgSO4 in a high hydrated state, resulting in a superior heat storage performance with an energy storage density of 772.9 kJ/kg and a water adsorption capacity of 0.37 g/g in a low to medium temperature range of 80–150 °C.

See publication (external link)

The UK government has set a target to reach net zero greenhouse gas emissions by 2050, and many other countries follow the same goal. In order to support the transition to net zero carbon future, Electric Vehicles (EV) can play a significant role. Providing a secure EV charging station is of high importance as the amount and type of data handled and transmitted via EV charging stations is growing and raising concerns both for the grid and consumers. The objective of this paper is to study the current landscape of EV charging stations in terms of cyber security, identify the cyber vulnerabilities, and present protocols and standards that can address cyber security challenges in such systems to provide a more secure charging infrastructure. Finally, this paper recommends the use of some security measures and techniques to mitigate cyber-attacks on EV charging infrastructure and alleviate the adverse impact of such attacks.

See publication (external link)

Security officers employ adversarial modelling techniques to drive analysis over complex attack surfaces. One technique for modelling safety and security is Attack Trees (AT) that uses logic gates to address the likelihood of malicious actions and outcomes. However, attack progression over time is not considered in AT analysis. To cope with this, the formalism of Boolean logic Driven Markov Processes (BDMP) extends AT where triggered transitions connect the sub-trees pertaining the hierarchy. BDMP is embedded with Markovian processes notions where modellers decorate transitions with likely timestamps to compute path probabilities. The time attackers take to complete any given malicious incursion stretches over a range of possibilities. Those durations are often difficult to cope due to a wealth of intangible characteristics such as adversaries' technical abilities, tool adequacy, quickness to devise vulnerability exploits, or countermeasures or defences in place in targeted infrastructures. The current BDMP analysis pipeline is sequential and generates a single output for one mission time. We propose BDMPathfinder, a tool that iterates over multiple durations to compute the totality of path attacks for BDMP models. We show its properties and trade-offs in a comprehensive case study exercising most common BDMP primitives by plotting the paths and probabilities altogether.

See publication (external link)

Thermochemical energy storage (TCES) may store heat for a theoretically indefinite amount of time at high energy storage density. It is an ideal means to achieve seasonal thermal energy storage (TES). Hydration at atmospheric pressure of inorganic hygroscopic salts has attracted much attention from the scientific community: TES in the range 30 °C-150 °C is achievable and suitable for domestic heating applications such a space-heating. While progress at both material and reactor scales have been made, there is still a lack of fundamental understanding of the relationships connecting the two, which is necessary in order to enable full TCES potential and develop technical solutions. We investigated inorganic salts K2CO3 and MgCl2, and composites consisting in these salts impregnated into vermiculite. Experimental measurements (dynamic vapour sorption) and numerical optimization of known solid-state kinetic models relevant for sorption were used to derive kinetic coefficients for different solid-state reaction kinetic models and to shed light on the possible rate-limiting mechanisms of the hydration of each material. Potassium carbonate (K2CO3) hydration was found to be kinetically hindered by what appears to be a diffusion barrier at the interparticle level. Impregnation of K2CO3 lead to a significantly improved hydration, controlled at 25 °C by nucleation and 40 °C by phase-boundary control according to the best fitting kinetic models. MgCl2 hydration was best modelled by first-order model and diffusion-type models, pointing towards intraparticle diffusion control. Finally, the hydration of MgCl2 impregnated into vermiculite was best modelled by phase-boundary control models, with no notable rate-limiting step change at different temperatures.

See publication (external link)

One of the biggest impacts of Net Zero will be the need to find alternatives to the (unabated) use of fossil fuels with their low cost, large capacity and long duration storage options, which still provide nearly all the flexibility and resilience that balance Great Britain’s energy systems. Currently, the heavy lifting in balancing Great Britain’s electricity and heat sectors is done by natural gas, capable of contributing 3-4 TWh towards managing imbalance daily, and over 100 TWh seasonally. This new research examines future imbalance in a ‘pure’ renewable electricity system, exclusively using various ratios of wind and solar generation, scaled to meet average electricity and heat demand. Imbalance calculations are based on actual measured generation and demand data for each day in the period 2015 to 2019 and not derived indirectly from meteorology. The results show: - Future orders of magnitude of system imbalance similar to those in the current system. - Electrifying heat would transfer imbalance into the electricity system doubling or trebling the scale of daily and cumulative imbalance levels, depending on the technology chosen. - The ‘optimum’ mix of wind and solar for minimising imbalance differs according to the timescale examined and whether the electricity sector is considered alone or together with the heat sector.

See publication (external link)

This book advances the reflexion into how temporary urbanism is shaping cities across the world. Temporary urbanism has become a core concept in urban development, and its application is increasingly crossing the borders of both the North and the Global South. There is a need to reflect upon the diverse ways of understanding and implementing the temporary in the production of space internationally and discuss what this means, for both research and practice. Divided into two sections, the book compiles and reflects upon the various attempts to reframe and reconceptualise temporary urbanism. The first section focuses on reframing and reconceptualising temporary urbanisms. It develops the argument that temporary urbanism allows a reinterrogation of the role of temporalities and non-permanence into the place-making process and hence in the production and reproduction of cities, including the adaptability of existing spaces and production of new spaces. While drawing upon different theoretical and conceptual framings (permeability, assemblage, rhythms, waiting, …), authors bring insights from various case studies: the Dublin Biennial (Ireland), temporary uses in Geneva (Switzerland), temporary urban settlements in sub-Saharan Africa, refugees’ camp in Beirut (Lebanon) and political protests in Skopje (Republic of Macedonia). The second section looks at unwrapping the complexity and diversity of temporary urbanisms. It aims at securing a better understanding of the complexity and diversity of temporary urbanism, including a dialogue between various experiences both in the Global North and in the Global South. It looks at the implications of temporary urbanism in the delivery of planning and considers how and by whom cities are governed and transformed. Again, a range of examples are mobilised by contributors spanning from temporary uses and projects in London (UK), Santiago (Chile), Paris (France), Vancouver (Canada), Barcelona (Spain), Budapest (Hungary), Beijing (China), Sao Paulo (Brazil) and Milwaukee (USA).

See publication (external link)

Soiling of solar module cover glass is a serious problem for solar asset managers. It causes a reduction in power output due to attenuation of the incident light, and reduces the return on investment. Regular cleaning is required to mitigate the effect but this is a costly procedure. The application of transparent hydrophobic, anti-soiling coatings to the cover glass is a promising solution. These coatings have low surface energy and contaminants do not adhere well. Even if soiling does remain on the coated surface, it is much more easily removed during cleaning. The performance of the coatings is determined using the water contact angle and roll-off angle measurements. However, although hydrophobic coatings hold out great promise, outdoor testing revealed degradation that occurs surprisingly quickly. In this study, we report on results using laboratory-based damp heat and UV exposure environmental tests. We used SEM surface imaging and XPS surface chemical analysis to study the mechanisms that lead to coating degradation. Loss of surface fluorine from the coatings was observed and this appeared to be a major issue. Loss of nanoparticles was also observed. Blistering of surfaces also occurs, leading to loss of coating material. This was probably due to the movement of retained solvents and was caused by insufficient curing. This mechanism is avoidable if care is taken for providing and carrying out carefully specified curing conditions. All these symptoms correlate well with observations taken from parallel outdoor testing. Identification of the mechanisms involved will inform the development of more durable anti-soiling, hydrophobic coatings for solar application.

See publication (external link)

Chapter in Understanding Cyber Threats and Attacks. In 1961, Leonard Kleinrock submitted to the MIT a PhD thesis entitled: “Information Flow in Large Communication Nets”1, an innovative idea for message exchanging procedures, based on the concept of post-office packet delivery procedures. It was the seed of ARPANET, a wide area data communication network, implemented in 1969, considered the origin of the Internet. At the end of the 1970’s, digital transmission and packet-switching allowed the building of ISDN (Integrated Services Data Networks). Voice and data were integrated in the same network, given birth to electronic offices combining computation and communication technologies. The electronic miniaturization and the popularization of micro-computers in the 1980’s, brought computer communication to home, allowing the integration and automation of many domestic tasks and access to some daily facilities from home. A new technological breakthrough came in 1989, when Tim Berners-Lee, a British scientist working at the European Organization for Nuclear Research (CERN), conceived the world wide web (www), easing the communication between machines around the world2. Nowadays, combining Kleinrock and Berners-Lee seminal ideas for network hardware and software, Internet became all pervasive in the daily life around the world, transforming the old telephone set into a small multipurpose computer. Consequently, human life radically changed. Our dependence on computer networks became undeniable and together with it, harmful programs or malwares, developedtodamagemachinesortostealinformation, represent permanent threat toindividuals and society. In computer science a new work research line emerged: cyber-security,which includes developing models, routines and software to protect machines and networks from malicious programs. This new discipline has attracted researchers to develop ideas for protecting people and corporations. Cyber-security is the object of this book, that presents hints about how the community is working to manage these threats: Mathematical models based on epidemiology studies, Control of malwares and virus propagation, Protection of essential service plants to assure reliability, the direct impact of virus and malwares over human activities and behavior, Government entities which are highly concerned with the necessary preventive actions. As cyber-security is a new and wide subject, the intention was to give a general idea of some points, leaving to the readers the task to go ahead.

See publication (external link)

Natural soiling and the subsequent requisite cleaning of photovoltaic (PV) modules result in abrasion damage to the cover glass. The durability of the front glass has important economic consequences, including determining the use of anti-reflective and/or anti-soiling coatings as well as the method and frequency of operational maintenance (cleaning). Artificial linear brush abrasion using Nylon 6/12 bristles was therefore examined to explore the durability of representative PV first-surfaces, i.e., the surface of a module incident to direct solar radiation. Specimens examined include silane surface functionalized-, roughened (etched)-, porous silica-coated-, fluoropolymer-coated-, and ceramic (TiO2 or ZrO2/SiO2/ZrO2/SiO2)-coated-glass, which are compared to monolithic-poly(methyl methacrylate) and -glass coupons. Characterization methods used in this study include: optical microscopy, ultraviolet–visible–near-infrared (UV-VIS-NIR) spectroscopy, sessile drop goniometry, white-light interferometry, atomic force microscopy (AFM), and depth-profiling X-ray photoelectron spectroscopy (XPS). The corresponding characteristics examined include: surface morphology, transmittance (i.e., optical performance), surface energy (water contact angle), surface roughness, scratch width and depth, and chemical composition, respectively. The study here was performed to determine coating failure modes; identify characterization methods that can detect nascent failures; compare the durability of popular contemporary coating materials; identify their corresponding damage characteristics; and compare slurry and dry-dust abrasion. This study will also aid in developing an abrasion standard for the PV industry.

See publication (external link)

Building retrofit is an important facet in the drive to reduce global greenhouse gas emissions. However, delivering building retrofit at scale is a significant challenge, especially in how to automate the process of building surveying. On-site survey by expert surveyors is the main approach in the industry. This can lead to a high workload if planning retrofit at a large-scale. An advanced vehicle-mounted data capturing system has been built to collect urban environmental multi-spectral data. The data contains substantial information that is essential in identifying building retrofit needs. Although the data capturing system is able to collect data in a highly-efficient manner, the data analysis is still a big data challenge to apply the system into delivering building retrofit plans. In this paper, a street-view building facade image segmentation model is designed as the foundation of the holistic data analysis framework. The model is developed on the deep learning-based semantic segmentation technology and uses an ensemble learning strategy. The object detection technology is fused into the model as an magnifier to improve the model performance on small objects and boundary predictions. The model has achieved state-of-the-art levels of accuracy on a built street-view building facade image dataset.

See publication (external link)

The need to accelerate the decarbonization of heating, as well as the rise of the ‘smart home’, mean that there is an increasing focus on the role of innovative consumer offerings in driving the shift to zero carbon domestic heating. In this context, Heat as a Service (HaaS) business models, which provide consumers with an agreed heating plan rather than simply paying for units of fuel, are receiving increased attention. This paper explores HaaS based on insights from facilitated group discussions with key stakeholders, and learning from HaaS trials, in the United Kingdom. Results identified evidence needs and research gaps related to: addressing issues of trust between consumers and suppliers, supportive policies, financing business models, and openness and interoperability of technology and data. Based on the findings, we propose policy and research recommendations to better understand the role of HaaS business models in decarbonization.

See publication (external link)

Next-generation concentrated solar power (CSP) plants are expected to work above the current temperature limit of 565 °C for the benefit of enhanced efficiency. This poses significant challenges in the construction materials, among others, in terms of corrosion. In this work, we investigate the spray-graphitization method to improve the compatibility of SS310 and SS347 with molten Li2CO3-Na2CO3-K2CO3 carbonate salt. Improved compatibility was observed due to the formation of protective carbonate or carbide layers on SS347 and SS310 surfaces, respectively. Detailed characterization of the corrosion products, including chemical reactions and wettability allowed the mechanism of anticorrosion protection to be proposed, which could be used for other construction materials in direct contact with high-temperature molten salts for next-generation CSP plants and beyond.

See publication (external link)

In this study, hiTRANTM wire matrix tube insert was used to improve the heat transfer deterioration of supercritical nitrogen (N2) in a heated tube caused by the effects of thermo-physical property variations and buoyancy force. Heat transfer experiments were carried out with N2 flowing upwardly in a vertical circular tube with and without the wire matrix insert under a sequence of experimental conditions including pressures of 35 and 40 bar, mass flow rate of 27.6 and 41.3 g/min and constant heat flux conditions at 6.8, 8.0 and 9.3 kW/m2, respectively. Experimental results show that N2 exhibits similar heat transfer behaviour when transiting across the pseudo-critical point as other fluids such as water and CO2. Due to the addition of the wire matrix insert, that intensified the overall fluid mixing in the test tube, the heat transfer performance of N2 was enhanced by more than 42% and up to 2.35 times while the pressure drop increase was negligible compared to the system inlet pressure. Moreover, it has been demonstrated that there might exist an optimum combination of experimental conditions leading to the maximum performance of the wire matrix insert. Furthermore, as the results show, with the Dittus-Boelter correlation and correlations for water and CO2 falling short of fitting the heat transfer data of N2, a heat transfer correlation, exclusively for N2 going through the pseudo-critical point is needed. The findings in this study also reveal that both supercritical N2 internal flow heat transfer and the use of wire matrix insert to enhance the deteriorated heat transfer of supercritical fluids are promising topics and require more significant attentions in future studies.

See publication (external link)

Molten salts-based nanofluids have been widely considered for Thermal Energy Storage (TES) applications due to their enhanced thermophysical properties. However, the application of such fluids faces many challenges, among which are the correct determination of their properties, stability, compatibility with construction materials and the overall environmental impact. In this work, we attempt to provide a comprehensive analysis of nanofluids based on nano-alumina and molten carbonate salt for the benefit of next-generation high-temperature TES applications. In particular, considerable statistics, cross-verification, novel preparation and characterization methods were applied to record ~12% increase of thermal conductivity, ~7% increase of heat capacity and ~35% increase of viscosity. It was demonstrated that such nanofluids have poor dispersion stability under static conditions; however, the enhanced thermophysical properties can be maintained by mechanical stimuli, e.g. mixing or redistribution. We show that some nanoparticles interact with typical construction materials such as stainless steel 310 by forming mixed oxides and considerably reducing the corrosion rates. An erosion study has been performed demonstrating negligible effect of nanoparticles even in the case of their strong agglomeration. Finally, life cycle analysis revealed that viscosity and preparation method of such nanofluids must be targeted to minimize the environmental impact.

See publication (external link)

This paper reviews the state-of-the-art knowledge of boiling heat transfer in binary mixtures with special emphasis placed on the heating and cooling industry. The advantage of using refrigerant mixtures over pure refrigerants include the enhancement of system coefficient of performance (COP), better match with the desired thermal load and being safer, more environmental-friendly refrigerants. In other words, the concept of using mixtures enables more flexible selection of suitable working fluids in particular thermal applications. The purpose of this review article aims to summarize the important published articles on boiling heat transfer in binary mixtures, as well as to identify limitations to existing studies, hereby providing guidelines, directing future studies and invoking further innovations of this well-established but still promising thermal management technique. The present article reviews straightforward on both pool boiling and flow boiling of binary mixtures in a systematic and comprehensive way. Specifically, in addition to the effects of fluid composition, heat flux, mass flux, pressure and heater surface condition, this article also reviews the effects of mass diffusion, heats from dilution and dissolution on pool boiling heat transfer of binary mixtures, along with the effects of flow orientation, flow regime and flow instability on flow boiling heat transfer of binary mixtures. Many papers reviewed herein relate to the heat transfer correlations towards boiling of binary mixtures.

See publication (external link)

Calcium-based materials are considered to be promising heat storage methods for the upcoming 3rd generation concentrated solar power systems (CSP) due to their high operation temperatures and energy storage densities. However, pure calcium carbonate (CaCO3) particles suffer from poor solar absorptance and stability. In this work, we successfully enhance solar absorptance, cycle stability, and decrease decomposition temperature, simultaneously, based on proposed doped CaCO3 particles. A fabrication method, which is cheap and suitable for large scale applications, is proposed based on doping Al and Fe elements into CaCO3 powders via sol–gel processes. The average solar absorptance is enhanced by about 560%, and the energy storage density decay rate after 50 cycles is prominently reduced to be as low as 4.5% from 35.5%. The decomposition temperature is reduced by 15 to 24 K depending on the atmospheres, and the decomposition kinetics of both doped and pure CaCO3 particles is found to follow the equation of phase boundary controlled reaction. The activation energy increases only slightly after doping, but will have a sharp increase when switching the atmosphere from N2 to pure CO2. This work paves the way to the design of high-performance calcium-based materials for next-generation high temperature thermal energy storage system.

See publication (external link)

The energy industry needs to take action against climate change by improving efficiency and increasing the share of renewable sources in the energy mix. On top of that, refrigeration, air conditioning , and heat pump equipment account for 25-30% of the global electricity consumption and will increase dramatically in the next decades. However, some waste cold energy sources have not been fully used. These challenges triggered an interest in developing the concept of cold thermal energy storage, which can be used to recover the waste cold energy, enhance the performance of refrigeration systems, and improve renewable energy integration. This paper comprehensively reviews the research activities about cold thermal energy storage technologies at sub-zero temperatures (from around −270°C to below 0°C). A wide range of existing and potential storage materials are tabulated with their properties. Numerical and experimental work conducted for different storage types is systematically summarized. Current and potential applications of cold thermal energy storage are analysed with their suitable materials and compatible storage types. Selection criteria of materials and storage types are also presented. This review aims to provide a quick reference for researchers and industry experts in designing cold thermal energy systems. Moreover , by identifying the research gaps where further efforts are needed, the review also outlines the progress and potential development directions of cold thermal energy storage technologies.

See publication (external link)

Publicly available electrical generation and interconnector data is combined to create a half-hourly dataset for Great Britain's electrical demand. The method uses Elexon data for power plants connected at the transmission level, monitored as part of the balancing mechanism, and combines these with the estimates for embedded generation for solar and wind generation from the system operator National Grid. The resulting dataset therefore has both transmission connected and distribution connected generation. Finally, to arrive at a closer representation of Great Britain's demand rather than its generation, the net imports are calculated from summing the values of all imports and exports. The resulting dataset termed ESPENI (Elexon Sum Plus Embedded Net Imports) keeps within 11 per cent of the official quarterly values from BEIS, which include auto generation that is not publicly available. The datasets are presented in both a cleaned and raw form and have been parsed to provide UTC and local time columns to be more easily utilised by a wider group of researchers.

See publication (external link)

Thermal energy storage (TES) technologies have been traditionally classified into sensible, latent and thermochemical categories. TES needs significant research efforts to address some fundamental challenges to reach its full potential. The hybridisation of TES technologies provides potentially a highly effective solution to the challenges. We present here a new concept, the 3 in 1 system, examining the feasibility, and the applied aspects of the newly proposed technology. The 3 in 1 system integrates the three known thermal storage methods of sensible heat, latent heat and thermochemical based TES into one system, providing three different operational configurations with cascading, charging integrated and discharging integrated working conditions. These different configurations offer controllability of TES charge/discharge processes while enhancing system-level efficiency. The proof of concept consists of a co-working matrix of a polymer as the phase change material (PCM), high-density polyethylene, and one of the most studied thermochemical material (TCM), MgSO4·7H2O. The feasibility of the composite containing 80–90 wt% of TCM was studied, over 15 cycles, for mechanical integrity, stability, energy stored and reaction kinetics. The results show that the system has a great potential for storing heat, up to 2 GJ∙m−3 and offers a wide working temperature range, from 30 °C to ∼150 °C. The combination of the PCM/TCM pairs give the composites mechanical integrity while accommodating the volume change and maintaining the structural stability during thermal cycling. This novel idea addresses some key technology gaps in TES particularly degradation and hence short life-span of TCM, cost-effectiveness and flexibility of the TCM based technology, thus offers potential paradigm shift to the thermal energy storage technology.

See publication (external link)

This paper presents a building-level analysis of almost 600,000 houses in London, using EPC data alongside 3DStock, a new highly detailed urban model. Focussing on the building envelope (specifically roofs, walls and glazing), the paper examines the current condition of the stock, as well as the opportunities for improving energy efficiency as defined by the EPC recommendations. Using highly detailed building level data, the areas of single-glazed windows, uninsulated walls, and poorly insulated lofts are quantified across the sample. It also examines the magnitude of this low-efficiency envelope that is not currently recommended for improvement in the EPCs. Finally, the paper estimates the total retrofit potential for houses in London.

See publication (external link)

In Brazil, the delivery of homes for low-inc ome households is dictated by costs rather than performance. Issues such as the impact of climate change, affordability of operational energy use, and lack of energy security are not taken into account, even though they can severely impact the occupants. In this work, the authors evaluated the thermal performance of two affordable houses as-built and after the integration of envelope improvements. A new replicable method to evaluate the cost-effectiveness of these improvements was proposed. The case study houses comprise the most common affordable housing type delivered widely across Brazil and a proposition of a better affordable housing solution, built in Porto Alegre, southern Brazil, integrating passive design strategies to increase thermal comfort. The findings reveal a potential for improving indoor thermal conditions by up to 76% and 73%, respectively, if costs are not a concern, and 40% and 45% with a cost increase of 12% and 9% if a comfort criterion of 20–25 °C was considered. Equations to estimate costs of improvements in affordable housing were developed. The authors concluded that there is a great scope for building envelope optimisation, and that this is still possible without significant impact on budget.

See publication (external link)

In this study, an experimental setup is developed to assess the thermal performance of a compact Latent Heat Thermal Energy Storage System (LHTESS) prototype during the charging/discharging stages. The LHTESS consists of a shell and horizontally oriented multi-tube heat exchanger and a commercially available paraffin wax RT44HC, which has a phase change temperature between 41°C and 43 °C as the energy storage medium. The testing campaign evaluated the influence of several operating conditions including the heat transfer fluid (HTF) volume flow rate and inlet temperature on the LHTESS power input and output, melting and solidification time and the energy stored and released. From the experimental results, it was observed that increasing the HTF inlet temperature has a significant effect on charging time compared to changing the HTF volume flow rate. When the LHTESS was charged using a fixed HTF inlet temperature of 60 °C, the charging process period took 296.3 min, 233.5 min, 204.8 min and 197.8 min when the HTF volume flow rate is 3.0, 4.5, 6.0 and 7.5 L/min. However, when the LHTESS was charged at HTF volume flow rate of 4.5 L/min, the results show that the charging completion time for HTF inlet temperatures of 55°C, 60 °C and 65°C are 316.6, 233.5 and 209.67 min, respectively. The results from the experimental analysis showed that the discharge time was significantly longer than the charging time due to an ever-growing layer of solid PCM around the external surface of heat exchanger throughout the discharging process which reduces the heat transfer coefficient between the PCM and HTF. This did not change substantially with the changing HTF volume flow rate.

See publication (external link)

Effective control of energy storage system (ESS), supplying an ancillary service to a grid, requires effective and critical calculation of state‐of‐charge (SoC). Charging and discharging values from battery operations are essential in calculating the efficiency and performance of a storage system. This information can also be a key to understand and forecast peak demand performance. Missing data is a real problem in any operations system, and it appears to be more common within powers systems due to sensor and/or network malfunctioning problems. Missing data imputation techniques have evolved in power systems research using smart meter data, but little research has gone into understanding how missing data can be best handled within storage management systems. This paper builds on a year's worth of charging and discharging data collected from a real 6MW/10MWh lithium‐ion storage battery deployed on the distribution network at Leighton Buzzard, UK. Using R Studio version (1.3.959‐1) open‐source software, eight selected imputation techniques were applied in identifying the best suited technique in replacing various missing data amounts and patterns. Findings from the study open up avenues for discussion and debate in identifying an appropriate imputation technique within the storage management context. The study also provides a pioneering lead in understanding the importance of decomposition in evaluating the right imputation technique.

See publication (external link)

The decarbonisation of residential building stock in the UK requires accessible tools that can reliably and rapidly model residential building power demands as a function of multiple low carbon technologies and building control schemes. Whilst a variety of modelling tools exists, these platforms are either intended for expert analysts, are not suited to rapid simulation (and therefore cumbersome at stock modelling scale) or are not flexible enough to allow analysis of detailed active control schemes. This work builds on a previously developed dynamic domestic building modelling tool developed in MATLAB/Simulink environment and intended for rapid generation of electrified heat demand profiles in buildings. The number of parameter inputs and time-resource required to prepare EWASP tool is several order of magnitude smaller than an equivalent EnergyPlus model, computational efficiency of this tool as well as its prediction accuracy are benchmarked against an equivalent E+ model. The EWASP model required 13 times less parameter input, reducing analyst time requirement and human effort. Both models produced similar trends of loads against external climatic changes for a Passivhaus case-study fabric while overall EWASP generated smaller ASHP electrical loads (4.4 kWh·m 2 ·yr) than EnergyPlus model (5.8 kWh·m 2 ·yr) which will be examined in future works. EWASP tool can assist assessment of the impact of fabric or HVAC retrofit and design and control scenario in buildings on the local distribution network and wider power grid

See publication (external link)

Temporary urbanism is an approach to reactivate urban spaces through short-term interventions in a range of urban contexts. In central São Paulo, the Luz and Santa Ifigênia neighbourhoods, characterized by deprivation of their physical environments and social structures, were the focus of this investigation. The Mungunzá Container Theatre and the General Osório Square, located within these neighbourhoods, were selected as case studies. Whilst the thermal performance of the container theatre itself was the main interest, in the case of the Square the fundamental issue was the environmental noise. The objective was to identify adequate strategies to improve environmental conditions in these locations in order to enhance positive social impact, and, then, contribute to the regeneration of these neighbourhoods. This research was based on fieldwork and analytical procedures of thermal and acoustic performances. In the container theatre building, the adoption of external shading and wider openings for ventilation reduced its indoor peak temperatures and delivered thermal comfort during the warmest period of the year. In the Square, sound absorber road surface material and an acoustic shell were proposed to reduce noise and promote better acoustic quality for outdoor performances.

See publication (external link)

Cyber‐Physical Systems (CPS) and Internet‐of‐Things (IoT) plus energy are the enabling technology of modern power systems also known as the Smart Grid (SG). A SG may consist of thousands of interconnected components communicating and exchanging data across layers that stretch beyond technical capabilities, for instance, markets and customer interactions. Cyber‐physical security is a major source of concern due to the high reliance of the SG on Information and Communication Technologies (ICT) and their widespread use. Addressing security requires developing modelling and simulation tools that approximate and replicate adversarial behaviour in the SG. These tools have in fact two simulators, one handling continuous power flows and another for capturing the discrete behaviour when communicating across CPS or IoT components. The technique of composing two models of computation in a global simulation of these coupled systems is called co‐simulation. Although there are many frameworks and tools for co‐simulation, the set of features for modelling cyber‐physical security incidents in the SG lacks thorough understanding. We present a systematic review of features and tools for co‐simulating these concerns in CPS. We also highlight and discuss research gaps with respect to the most used tools in industry and academia and comment on their relevant features.

See publication (external link)

A brief history is provided of models of energy use in the UK building stock, with the focus on the non-domestic sector. This history leads to an account of the development, since 2009, of the 3DStock method for modelling complete building stocks, both domestic and non-domestic. The paper explains how 3DStock models are built and the data sources used. Special emphasis is placed on the relationship of premises (the floorspace occupied by organisations) to buildings. Energy use may be metered at the level of premises, buildings or groups of buildings. Representing the patterns in which premises relate to buildings is therefore crucial to the modelling process, and in particular to the precise measurement of energy intensities. Applications of 3DStock models in building science and policy tools are reviewed, including the London Building Stock Model (LBSM), delivered to the Greater London Authority (GLA) in 2020. This ‘digital twin’ can be used for the monitoring, simulation and analysis of the building stock. Implications for research and policy are discussed, particularly for energy epidemiology, density, high-rise buildings, retrofit potential, energy-use intensity and benchmarking. Data are in place to extend 3DStock modelling to the whole of England and Wales.

See publication (external link)

The London Building Stock Model, commissioned by the Greater London Authority (GLA) contains detailed data on every separate domestic and non-domestic building in Greater London. It includes three dimensional information about buildings including their heights, volumes, wall areas, floor areas and the distribution of activities between different floors. These data are drawn from University College London Energy Institute’s existing 3DStock model of London. Within the model information is attached on the ages of buildings, their materials of construction, and (in some cases) their servicing systems. Energy Performance Certificates (EPCs) and Display Energy Certificates (DECs) are also attached to premises and dwellings along with gas and electricity energy consumption. Buildings in London are responsible for over 65% of the total carbon dioxide (CO2) emissions attributed to the Greater London region in 2016. Reducing CO2 emissions that can be attributed to buildings is the key focus of this work in line with the GLA’s ambition to dramatically reduce these overall CO2 emissions; aiming to make London a zero-carbon city by 2050. Improving the energy performance of existing buildings has to be a key strategy if the overall CO2 emissions are to be reduced. Knowing the characteristics and current energy efficiency of the building stock is the first step towards reducing direct and indirect CO2 emissions from these buildings. Collecting the data is one challenge, but making sense of these huge quantities of data is a bigger challenge. Structuring the data can help here and so for this paper we present the evaluation of energy efficiency of buildings in London using urban density to aggregate the data. Energy efficiency is measured from both EPCs and energy consumption. Some of the existing measures that might influence current energy efficiency are then shown at different levels of urban density. Finally, in order to address the improvement of the energy efficiency we quantify the ‘potential’ improvements of these buildings (according to the EPC recommendations) and hence the suitability of different retrofit solutions, again aggregated by urban density. The results show that energy use intensity decreases as urban density increases; that urban density has some influence on existing efficiency measures and finally that most of the measures of retrofit potential change with increasing urban density.

See publication (external link)

With the recent removal of the solar PV feed-in tariff on ≤4 kWp arrays, installation of domestic rooftop PV has become significantly less commercially feasible in the UK. Whilst alternative trading schemes are beginning to emerge, the adequacy of their return on investment is questionable. However, the extent to which installation may need to be subsidised has not yet been quantified. Furthermore, the extent to which increased peer-to-peer trading could contribute to network constraints, and the environmental and economic costs of managing such schemes, have not been examined extensively. In this paper, the subsidy required to encourage a rooftop PV uptake rate of 0.5% homeowners/year is determined and the costs of constraint management are calculated for various network topologies. The problems presented are solved using time series analysis, power flow simulations, and optimisation processes with Monte Carlo methods. It was found that P2P trading is the most promising post subsidy revenue stream, reducing the required feed-in tariff from £0.14 to £0.10 for systems installed in 2020. Furthermore, it was found that with P2P trading, requirement for feed-in tariff support should end by 2032. Reconductoring was the most economically effective constraint management strategy, costing £50 k to £200 k less than curtailment when applied to 29 networks over 30 years. From an environmental perspective, it was found that reconductoring had a carbon footprint 2 orders of magnitude lower than curtailment & battery storage.

See publication (external link)

Alongside a mean global rise in temperature, climate change predictions point to an increase in heat waves and an associated rise in heat-related mortality. This suggests a growing need to ensure buildings are resilient to such events. Unfortunately, there is no agreed way of doing this, and no standard set of heatwaves for scientists or engineers to use. In addition, in all cases, heat waves are defined in terms of external conditions, yet, as the Paris heat wave of 2003 showed, people die in the industrialised world from the conditions inside buildings, not those outside. In this work, we reverse engineer external temperature time series from monitored conditions within a representative set of buildings during a heat wave. This generates a general probabilistic analytical relationship between internal and external heatwaves and thereby a standard set of events for testing resilience. These heat waves are by their simplicity ideal for discussions between clients and designers, or for the setting of national building codes. In addition, they provide a new framework for the declaration of a health emergency.

See publication (external link)

Globally, a primary concern is whether green office buildings perform as promised in terms of providing better indoor environment quality (IEQ) for employees, which may affect their satisfaction and work performance. In the Middle East, although there has been renewed interest in green building design, post occupancy evaluation of performance has never been conducted to-date, and evidence of actual occupant perception in green and non-green buildings is still ambiguous. Hence, we present the first study on IEQ performance in the Middle East. We show that Jordan can be taken as a representative example and systematically compare five “green” office buildings (representing 71% of all green-certified office buildings) against eight comparable conventional office buildings (CBs). Detailed bi-lingual survey data on perceived IEQ (n = 502) and work performance are accompanied by high-resolution continuous physical measurements of air temperature + relative humidity (n = 83) and CO2 concentrations (n = 21) with periodic measurements of mean radiant temperature and air speed, covering two typical summers and one typical winter. Results show both buildings types comply with design standards for indoor CO2 levels, while thermal comfort in green buildings is better than in CBs. However, CBs have a higher overall occupant satisfaction of IEQ. Work performance measured as absolute and relative absenteeism was slightly higher in CBs, with no significant differences in relative and absolute presenteeism between the two buildings types. These findings challenge the notion that green buildings improve occupant satisfaction and work performance over CBs and suggest the need for a better understanding of the performance-satisfaction gap.

See publication (external link)

The disparity between disciplinary approaches to bioinspired innovation has created a cultural divide that is stifling to the overall advancement of the approach for sustainable societies. This paper aims to advance the effectiveness of bioinspired innovation processes for positive benefits through interdisciplinary communication by exploring the epistemological assumptions in various fields that contribute to the discipline. We propose that there is a shift in epistemological assumptions within bioinspired innovation processes at the points where biological models derived from reductionist approaches are interpreted as socially-constructed design principles, which are then realized in practical settings wrought with complexity and multiplicity. This epistemological shift from one position to another frequently leaves practitioners with erroneous assumptions due to a naturalistic fallacy. Drawing on examples in biology, we provide three recommendations to improve the clarity of the dialogue amongst interdisciplinary teams. (1) The deliberate articulation of epistemological perspectives amongst team members. (2) The application of a gradient orientation towards sustainability instead of a dichotomous orientation. (3) Ongoing dialogue and further research to develop novel epistemological approaches towards the topic. Adopting these recommendations could further advance the effectiveness of bioinspired innovation processes to positively impact social and ecological systems.

See publication (external link)

Buildings contribute a significant portion of global greenhouse gas emissions and have the potential for large-scale impact reductions. Reducing the whole-life impacts of buildings is critical for creating a net-zero carbon built environment. For this to be achieved, the whole-life carbon impacts of design decisions must be considered during the building design process. A systematic review of academic literature was conducted to assess how life cycle assessment (LCA) is incorporated at various stages of the building design process, and what improvements are needed to support net-zero carbon design. The review compiled 274 papers that were published up to the end of 2019, of which 108 were subject to detailed review following screening. The review found that LCA is generally used late in the design process, when it is too late to greatly influence the design. Incorporating LCA with either building information modelling or life cycle costing is seen to have the same challenges as undertaking a traditional LCA. Parametric methods show promise for design development, but tools and algorithms require further verification and regionalisation to be implemented throughout industry. The use of benchmarks, target values and other pre-populated information can be used to incorporate life-cycle thinking without the need to undertake a detailed LCA. The review has demonstrated that LCA continues to face barriers, in both methods and practice, preventing its ability to guide early-stage design decisions and have a large impact on the environmental performance of buildings.

See publication (external link)

In most industrialized countries, the buildings sector is the largest contributor to energy consumption and associated carbon emissions. These emissions can be reduced by a combination of energy efficiency and the use of building integrated renewables. Additionally, either singularly or as a group, buildings can provide energy network services by timing their use and production of energy. Such grid-aware or grid-responsive buildings have been termed Active Buildings. The recent UK Government investment of £36m in the Active Building Centre is a demonstration that such buildings are of considerable interest. One problem with the concept, however, is that there is no clear definition of Active Buildings, nor a building code to design or research against. Here we develop and test an initial novel code, called ABCode1. It is based on the need to encourage: (i) the minimisation of energy consumption; (ii) building-integrated generation; (iii) the provision of grid services; and (iv) the minimisation of embodied carbon. For grid services, we find that a lack of a precise, quantifiable measure, or definition, of such services means that for the time being, theoretical hours of autonomy of the building is the most reasonable proxy for these services within such a code.

See publication (external link)

The Smart Grid (SG) is a Cyber-Physical System (CPS) considered a critical infrastructure divided into cyber (software) and physical (hardware) counterparts that complement each other. It is responsible for timely power provision wrapped by Information and Communication Technologies (ICT) for handling bi-directional energy flows in electric power grids. Enacting control and performance over the massive infrastructure of the SG requires convenient analysis methods. Modelling and simulation (M&S) is a performance evaluation technique used to study virtually any system by testing designs and artificially creating 'what-if' scenarios for system reasoning and advanced analysis. M&S avoids stressing the actual physical infrastructure and systems in production by addressing the problem in a purely computational perspective. Present work compiles a non-exhaustive list of tools for M&S of interest when tackling SG capabilities. Our contribution is to delineate available options for modellers when considering power systems in combination with ICT. We also show the auxiliary tools and details of most relevant solutions pointing out major features and combinations over the years.

See publication (external link)

Cyber-Physical Systems (CPS) are present in many settings addressing a myriad of purposes. Examples are Internet-of-Things (IoT) or sensing software embedded in appliances or even specialised meters that measure and respond to electricity demands in smart grids. Due to their pervasive nature, they are usually chosen as recipients for larger scope cyber-security attacks. Those promote system-wide disruptions and are directed towards one key aspect such as confidentiality, integrity, availability or a combination of those characteristics. Our paper focuses on a particular and distressing attack where coordinated malware infected IoT units are maliciously employed to synchronously turn on or off high-wattage appliances, affecting the grid's primary control management. Our model could be extended to larger (smart) grids, Active Buildings as well as similar infrastructures. Our approach models Coordinated Load-Changing Attacks (CLCA) also referred as GridLock or BlackIoT, against a theoretical power grid, containing various types of power plants. It employs Continuous-Time Markov Chains where elements such as Power Plants and Botnets are modelled under normal or attack situations to evaluate the effect of CLCA in power reliant infrastructures. We showcase our modelling approach in the scenario of a power supplier (e.g. power plant) being targeted by a botnet. We demonstrate how our modelling approach can quantify the impact of a botnet attack and be abstracted for any CPS system involving power load management in a smart grid. Our results show that by prioritising the type of power-plants, the impact of the attack may change: in particular, we find the most impacting attack times and show how different strategies impact their success. We also find the best power generator to use depending on the current demand and strength of attack.

See publication (external link)

As Internet of Things (IoT) technologies enable greater communication between energy assets in smart cities, the operational coordination of various energy networks in a city or district becomes more viable. Suitable tools are needed that can harness advanced control and machine learning techniques to achieve environmental, economic and resilience objectives. In this paper, an energy management tool is presented that can offer optimal control, scheduling, forecasting and coordination services to energy assets across a district, enabling optimal decisions under user-defined objectives. The tool presented here can coordinate different sub-systems in a district to avoid the violation of high-level system constraints and is designed in a generic fashion to enable transferable use across different energy sectors. The work demonstrates the potential for a single open-source optimisation framework to be applied across multiple energy vectors, providing local government the opportunity to manage different assets in a coordinated fashion. This is shown through case studies that integrate low-carbon communal heating for social housing with electric vehicle charge-point management to achieve high-level system constraints and local government objectives in the borough of Greenwich, London. The paper illustrates the theoretical methodology, the software architecture and the digital twin-based testing environment underpinning the proposed approach.

See publication (external link)

In this study, the thermal performance of latent heat thermal energy storage system (LHTESS) prototype to be used in a range of thermal systems (e.g., solar water heating systems, space heating/domestic hot water applications) is designed, fabricated, and experimentally investigated. The thermal store comprised a novel horizontally oriented multitube heat exchanger in a rectangular tank (forming the shell) filled with 37.8 kg of phase change material (PCM) RT62HC with water as the working fluid. The assessment of thermal performance during charging (melting) and discharging (solidification) was conducted under controlled several operational conditions comprising the heat transfer fluid (HTF) volume flow rates and inlet temperatures. The experimental investigations reported are focused on evaluating the transient PCM average temperature distribution at different heights within the storage unit, charging/discharging time, instantaneous transient charging/discharging power, and the total cumulative thermal energy stored/released. From the experimental results, it is noticed that both melting/solidification time significantly decreased with increase HTF volume flow rate and that changing the HTF inlet temperature shows large impacts on charging time compared to changing the HTF volume flow rate. During the discharging process, the maximum power output was initially 4.48 kW for HTF volume flow rate of 1.7 L/min, decreasing to 1.0 kW after 52.3 min with 2.67 kWh of heat delivered. Based on application heat demand characteristics, required power levels and heat demand can be fulfilled by employing several stores in parallel or series.

See publication (external link)

‘Community Energy’ refers to people working together to reduce and manage energy use and increase and support local energy generation. It has the potential to support the infrastructural, social and cultural changes needed to reduce the impact of climate change and increase energy security. The core part of community energy initiatives is people; therefore, successful engagement strategies are essential. SCENe (Sustainable Community Energy Networks) was a research and development project focused on community energy application in a real-world setting involving in its first phase 44 new homes built along the banks of Nottingham’s River Trent (UK). The project team adopted a variety of established and innovative engagement strategies including website and social media channels, an online platform, a physical community energy hub where meetings and workshops were held and an interactive virtual energy model could be accessed, and in-home smart voice-controlled and visual technologies. The influence of the project and the effectiveness of the engagement tools to generate behaviour changes were investigated through a survey, workshops and interviews. The results suggest that engagement with SCENe increased awareness of energy issues and supported wider participation in community initiatives.

See publication (external link)

Airtightness refers to the amount of air leakage through a building’s envelope. This uncontrolled exchange of air between inside and outside, either infiltration or exfiltration, may lead to thermal discomfort. Nevertheless, little or no attention has been given to airtightness in some countries including Brazil. In Brazil, a range of different strategies are suitable to achieve thermal comfort depending on the several climatic regions. In those regions where winter conditions are noticeable, such as in São Paulo, airtightness is a key parameter, but it has been historically overlooked. In this work, the authors deployed the innovative Pulse test methodology to determine airtightness levels for the first time in Brazil, in the city of São Paulo. Three representative multifamily residential buildings dating from the 1970s, 1980s and 2000s were measured, and the results’ values widely ranged from 1 to 5.7 h−1, at 4 Pa. Next, dynamic building simulations were conducted using measured and representative airtightness values (converted to infiltration) to understand the contribution of this variable on the thermal comfort. The results suggested that up to 9% improvement in the thermal comfort levels could be achieved by adopting 1 h−1 as maximum infiltration, and up to 14% by adopting 0.5 h−1.

See publication (external link)

The measures to control the spread of COVID-19 are unparalleled, and this is already having an effect on Britain’s energy system. There have been massive short-term changes in the past: for instance the temporary imposition of a three-day week in the 1970s may have had an even greater overall effect, but this was due to industrial action in the coal sector affecting the supply of energy. This time, the disruption is on the demand side – the energy is still available, but the demand for it has reduced.

See publication (external link)

In 2010, Great Britain generated 75% of its electricity from coal and natural gas. But by the end of the decade*, these fossil fuels accounted for just 40%, with coal generation collapsing from the decade’s peak of 41% in 2012 to under 2% in 2019.

See publication (external link)

Martin Mayfield (University of Sheffield) explains the importance of Urban Scale Digital Twins for providing a holistic approach to urban and infrastructure design, operation and future proofing.

See publication (external link)

Data collection is a fundamental component in the study of energy and buildings. Errors and inconsistencies in the data collected from test environment can negatively influence the energy consumption modelling of a building and other control and management applications. This paper addresses the gap in the current study of missing data treatment. It presents a comparative study of eight methods for imputing missing values in building sensor data. The data set used in this study, are real data collected from our test bed, which is a living lab in the Newcastle University. When the data imputation process is completed, we used Mean Absolute Error, and Root Mean Squared Error methods to evaluate the difference between the imputed values and real values. In order to achieve more accurate and robust results, this process has been repeated 1000, and the average of 1000 simulation is demonstrated in this paper. Finally, it is concluded that it is necessary to identify the percentage of missing data before selecting the proper imputation method, in order to achieve the best result.

See publication (external link)

Within the context of the Smart City, the need for intelligent approaches to manage and coordinate the diverse range of supply and conversion technologies and demand applications has been well established. The wide-scale proliferation of sensors coupled with the implementation of embedded computational intelligence algorithms can help to tackle many of the technical challenges associated with this energy systems integration problem. Nonetheless, barriers still exist, as suitable methods are needed to handle complex networks of actors, often with competing objectives, while determining design and operational decisions for systems across a wide spectrum of features and time-scales. This review looks at the current developments in the smart energy sector, focussing on techniques in the main application areas along with relevant implemented examples, while highlighting some of the key challenges currently faced and outlining future pathways for the sector. A detailed overview of a framework developed for the EU H2020 funded Sharing Cities project is also provided to illustrate the nature of the design stages encountered and control hierarchies required. The study aims to summarise the current state of computational intelligence in the field of smart energy management, providing insight into the ways in which current barriers can be overcome.

See publication (external link)